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Group-based forecasting?: A social psychological analysis

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  • Kerr, Norbert L.
  • Tindale, R. Scott
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    Abstract

    The potential of group (vs. individual) forecasting is analyzed from the perspective of the social psychology of groups. The social decision scheme theory (SDST) is summarized, and several simulations are presented to demonstrate the dependence of group aggregation accuracy upon factors such as group size, the accuracy and distribution of individual forecasts, and shared representations of the forecasting problem. Many advantages and disadvantages of group aggregation are identified and related to four generic methods of group aggregation (statistical aggregation, prediction markets, the Delphi method, and face-to-face discussion). A number of aspects of forecasting problems are identified which should govern whether or not group forecasting can be relied upon, and if so, what aggregation method should be used.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0169207010000166
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    Bibliographic Info

    Article provided by Elsevier in its journal International Journal of Forecasting.

    Volume (Year): 27 (2011)
    Issue (Month): 1 ()
    Pages: 14-40

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    Handle: RePEc:eee:intfor:v:27:y:2011:i:1:p:14-40

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    Web page: http://www.elsevier.com/locate/ijforecast

    Related research

    Keywords: Delphi; Prediction markets; Aggregation; Face-to-face groups; Social decision schemes;

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    Cited by:
    1. Agrawal, Rashmi & Nanda, S.K., 2013. "Integrated Approach to Human Resource Forecasting: An Exercise in Agricultural Sector," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 26(2).
    2. Kauko, Karlo & Palmroos, Peter, 2014. "The Delphi method in forecasting financial markets— An experimental study," International Journal of Forecasting, Elsevier, vol. 30(2), pages 313-327.
    3. Wright, George & Rowe, Gene, 2011. "Group-based judgmental forecasting: An integration of extant knowledge and the development of priorities for a new research agenda," International Journal of Forecasting, Elsevier, vol. 27(1), pages 1-13, January.

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